Hi, everyone, I am using limma to analyse an agilent one-color array experiment, and have run into difficulties with duplicateCorrelation. My experiment is as follows: single color agilent arrays, 4 WT samples, and 3 samples of each of 4 treatment (treatments 1-4). I also have technical replicates (replicated once) for each sample. There are therefore 32 files. The targets file looks like this: ? ?? SampleNumber????????????????? FileName Condition Notes 1???????????? 1? RH_02_1_77_Oct11_1_1.txt??? Treat1?? 1.1 2???????????? 2? RH_02_1_77_Oct11_2_1.txt??? Treat1?? 1.2 3???????????? 3? RH_04_1_77_Oct11_1_1.txt??? Treat1?? 2.1 4???????????? 4? RH_07_1_77_Oct11_1_1.txt??? Treat1?? 2.2 5???????????? 5? RH_04_1_77_Oct11_1_2.txt??? Treat1?? 3.1 6???????????? 6? RH_07_1_77_Oct11_1_2.txt??? Treat1?? 3.2 7???????????? 7? RH_04_1_77_Oct11_1_3.txt??? Treat2?? 4.1 8???????????? 8? RH_07_1_77_Oct11_1_3.txt??? Treat2?? 4.2 9???????????? 9? RH_04_1_77_Oct11_1_4.txt??? Treat2?? 5.1 10?????????? 10? RH_07_1_77_Oct11_1_4.txt??? Treat2?? 5.2 11?????????? 11? RH_04_1_77_Oct11_2_1.txt??? Treat2?? 6.1 12?????????? 12? RH_07_1_77_Oct11_2_1.txt??? Treat2?? 6.2 13?????????? 13 US0_05_1_77_Oct11_1_1.txt??? Treat3?? 7.1 14?????????? 14? RH_01_1_77_Oct11_1_1.txt??? Treat3?? 7.2 15?????????? 15 US0_05_1_77_Oct11_1_2.txt??? Treat3?? 8.1 16?????????? 16? RH_01_1_77_Oct11_1_4.txt??? Treat3?? 8.2 17?????????? 17? RH_02_1_77_Oct11_1_2.txt??? Treat3?? 9.1 18?????????? 18? RH_02_1_77_Oct11_2_2.txt??? Treat3?? 9.2 19?????????? 19 US0_05_1_77_Oct11_1_3.txt??? Treat4? 10.1 20?????????? 20? RH_01_1_77_Oct11_1_2.txt??? Treat4? 10.2 21?????????? 21 US0_05_1_77_Oct11_1_4.txt??? Treat4? 11.1 22?????????? 22? RH_01_1_77_Oct11_1_3.txt??? Treat4? 11.2 23?????????? 23? RH_04_1_77_Oct11_2_2.txt??? Treat4? 12.1 24?????????? 24? RH_07_1_77_Oct11_2_2.txt??? Treat4? 12.2 25?????????? 25 US0_05_1_77_Oct11_2_1.txt??????? WT? 13.1 26?????????? 26? RH_01_1_77_Oct11_2_1.txt??????? WT? 13.2 27?????????? 27 US0_05_1_77_Oct11_2_2.txt??????? WT? 14.1 28?????????? 28? RH_01_1_77_Oct11_2_2.txt??????? WT? 14.2 29?????????? 29 US0_05_1_77_Oct11_2_3.txt??????? WT? 15.1 30?????????? 30? RH_01_1_77_Oct11_2_3.txt??????? WT? 15.2 31?????????? 31 US0_05_1_77_Oct11_2_4.txt??????? WT? 16.1 32?????????? 32? RH_01_1_77_Oct11_2_4.txt??????? WT? 16.2 I run the following commands to process the data and create the design: RG <- read.maimages(targets, columns = list(G = "gMedianSignal", Gb = "gBGMedianSignal", R = "gProcessedSignal",Rb = "gIsPosAndSignif"), annotation = c("Row", "Col","FeatureNum","ControlType","ProbeName")) RG <- backgroundCorrect(RG, method="normexp", offset=1) E <- normalizeBetweenArrays(RG, method="Aquantile") E.avg <- avereps(E, ID=E$genes$ProbeName) f <- factor(targets$Condition, levels = unique(targets$Condition)) design <- model.matrix(~0 + f) colnames(design) <- levels(f) ? The problem arises when I do the duplicateCorrelation. biolrep <- c(1,1,2,2,3,3,4,4,5,5,6,6,7,7,8,8,9,9,10,10,11,11,12,12,13, 13,14,14,15,15,16,16) corfit <- duplicateCorrelation(E.avg, design, ndups=1,block=biolrep) fit <- lmFit(E.avg$A, design, block=biolrep, cor=corfit$consensus.correlation) contrast.matrix <- makeContrasts("Treat1-WT",levels=design)??????????? ?????????????????????????????????????????????????fit2 <- contrasts.fit(fit, contrast.matrix) fit2 <- eBayes(fit2) topTable(fit2, adjust="BH", coef="Treat1-WT", genelist=E.avg$genes, number=10) Whereas I would expect the corfit$consensus.correlation to be generally very positive, I get the value 0.01385223.?Does anyone have any suggestions? Any help would be appreciated ? Jabez